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Titlebook: Advances in Visual Computing; Third International George Bebis,Richard Boyle,Tom Malzbender Conference proceedings 2007 Springer-Verlag Be

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31#
發(fā)表于 2025-3-26 21:52:02 | 只看該作者
32#
發(fā)表于 2025-3-27 03:10:16 | 只看該作者
33#
發(fā)表于 2025-3-27 06:29:47 | 只看該作者
Superpixel Analysis for Object Detection and Tracking with Application to UAV Imageryibutes derived from the Hough transform. We describe preliminary results on image sequences taken from low-flying aircraft in which object categories are relevant to UAVs, consisting of sky, ground, and navigationally-useful ground features such as roads and pipelines.
34#
發(fā)表于 2025-3-27 12:29:41 | 只看該作者
A Novel Optical Tracking Algorithm for Point-Based Projective Invariant Marker Patternsatterns inside the same tracking area, in real time. The algorithm only needs image coordinates of markers to perform the identification of marker patterns. For grouping the dispersed markers that appear in the image, the algorithm uses a “divide and conquer” strategy to segment the image and give some neighborhood reference among markers.
35#
發(fā)表于 2025-3-27 16:08:17 | 只看該作者
36#
發(fā)表于 2025-3-27 21:46:24 | 只看該作者
Pamela Elizabeth Clark,Chuck Clarknces of body poses performed during motion. Our approach uses these trajectories in order to classify human actions. The approach was checked on HumanEva data set as well as on our own one. The results and the comparison to other methods are presented.
37#
發(fā)表于 2025-3-27 23:16:29 | 只看該作者
https://doi.org/10.1007/978-3-319-01255-1of the data. We propose a hierarchical coding method to further compress the cubic control points. We compare our method with wavelet compression methods, which have the best compression rates to date. Experiments show that our method, relative to this work, can achieve about a 65% higher compression rate at the same approximation level.
38#
發(fā)表于 2025-3-28 03:49:34 | 只看該作者
https://doi.org/10.1007/978-3-642-18562-5that capture important attributes of the shape and mutual relationship of strokes. These features are statistically well-behaved and enable robust classification with Support Vector Machines (SVM). We conclude by presenting a concrete implementation of these techniques in an interface for driving facial expressions.
39#
發(fā)表于 2025-3-28 09:57:21 | 只看該作者
40#
發(fā)表于 2025-3-28 13:31:13 | 只看該作者
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